Familial Multigenerational Housing: A Resurgent Typology

Majority of housing models in the United States do not address the financial crisis and care responsibilities that burden many contemporary families. While many cultures practice multigenerational living as a means to ease some of these burdens, the homes in which this lifestyle is practiced are not designed for this purpose. As the population of Houston continues to grow, its urban landscape will need to adapt and ultimately densify as it cannot continue to expand its city limits indefinitely. Through the development of middle scale familial multigenerational housing complexes, residents of the city can transition into denser housing models while also easing some of their current financial and care responsibilities

Collaborative Settler Colonialism: Japanese Migration to Brazil in the Age of Empires

Though Japanese migration to Brazil started only at the turn of the twentieth century, Brazil is now the country with the largest ethnic Japanese population outside Japan. Collaborative Settler Colonialism examines this history as a central chapter of both Brazil’s and Japan’s processes of nation and empire building and, crucially, as a convergence of their settler colonial projects. Inspired by American colonialism and the final conquest of the U.S. Western frontier, Brazilian and Japanese empire builders collaborated to bring Japanese migrants to Brazil, which had the outcome of simultaneously dispossessing Indigenous Brazilians of their land and furthering the expansion of Japanese land and resource possession abroad. Bringing discourses of Latin American and Japanese settler colonialism into rare dialogue with each other, this book offers new insight into the Japanese empire, the history of immigration to Brazil and Latin America, and the past and present of settler colonialism.Fondren Librar

Engineering Glucose Enzymes Through Domain Insertion for Adaptive Bioelectronic Sensors

Biosensors are essential in diagnostics, monitoring, and therapeutics. A major example is the glucometer, which effectively utilizes glucose-oxidizing enzymes to generate accurate electrical signals that report blood sugar levels. This bioelectrochemical sensor’s affordability, manufacturability, and suitability for patient-side use make glucose enzymes highly appealing for broader sensing applications. Although existing studies have explored mutagenizing glucose redox enzymes to enhance their stability and activity, significant obstacles remain in repurposing these enzymes to detect other biomarkers. These challenges stem from an incomplete understanding of glucose enzyme design and the limited effectiveness of current protein engineering approaches. This thesis addresses these challenges by using pyrroloquinoline quinone glucose dehydrogenase (PQQ-GDH) as a robust platform for glucose-dependent oxidoreductase applications. Through comprehensive methods developed to identify structural elements crucial to its function, this work demonstrates the repurposing of PQQ-GDH to produce electrochemical output for non-glucose analytes. Additionally, a high-throughput screening system is introduced to accelerate the development of a broad range of bioelectronic sensors. In Chapter 2, we integrate small peptide sequences into PQQ-GDH to investigate the structure-sequence-function relationships at various structural levels. In Chapter 3, we engineer PQQ-GDH conformational switches to create electronic sensors capable of detecting cancer therapeutics in blood samples, pushing the boundaries of traditional glucose sensing. In Chapter 4, we establish a high-throughput selection system for glucose enzyme variants by manipulating glucose metabolism and NADPH regeneration in E. coli through targeted knockouts. Our research explores multiple strategies for functionalizing PQQ-GDH to enhance bioelectronic diagnostics. These findings provide critical insights into how the structure and sequence of PQQ-GDH influence its function—particularly at the active site and dimerization interface, which are essential for enzyme activity and stability. When integrated onto electrode interfaces, our functionalized PQQ-GDH variants demonstrate a significant electrical response to the cancer therapeutic 4-hydroxytamoxifen in blood. This advancement lays a solid foundation for real-time, point-of-care diagnostics in therapeutic monitoring. Additionally, our innovative growth complementation assay enriches enzyme variants in direct proportion to their activity levels, establishing a novel selection method for variants that exhibit superior performance. These contributions advance biosensing technologies and significantly expand the application scope of bioelectrochemical systems. We are paving the way for reliable point-of-care diagnostic devices and therapeutic monitoring platforms that promise to transform future healthcare solution

Incorporating Anti-Racist Pedagogy into a Foreign Language Classroom

Conference presentation on anti-racist pedagog

Taming Data and Transformers for Audio Generation

Generating ambient sounds is a challenging task due to data scarcity and often insufficient caption quality, making it difficult to employ large-scale generative models for the task. In this work, we tackle this problem by introducing two new models. First, we propose AutoCap, a high-quality and efficient automatic audio captioning model. By using a compact audio representation and leveraging audio metadata, AutoCap substantially enhances caption quality, reaching a CIDEr score of 83.2, marking a 3.2% improvement from the best available captioning model at four times faster inference speed. Second, we propose GenAu, a scalable transformer-based audio generation architecture that we scale up to 1.25B parameters. Using AutoCap to generate caption clips from existing audio datasets, we demonstrate the benefits of data scaling with synthetic captions as well as model size scaling. When compared to state-of-the-art audio generators trained at similar size and data scale, GenAu obtains significant improvements of 4.7% in FAD score, 22.7% in IS, and 13.5% in CLAP score, indicating significantly improved quality of generated audio compared to previous works. Moreover, we propose an efficient and scalable pipeline for collecting audio datasets, enabling us to compile 57M ambient audio clips, forming AutoReCap-XL, the largest available audio-text dataset, at 90 times the scale of existing ones. Our code, model checkpoints, and dataset will be made publicly available upon acceptance

Development of experimental platforms for ultra-high- throughput exploration of complex genetic design spaces

Cells sense and process signals from their environment to execute a diverse array of tasks, ranging from proliferation and differentiation to programmed cell death. Inspired by the capabilities of biological systems to carry out sophisticated computations, the field of synthetic biology aims to use nucleic acid-encoded “synthetic” regulatory programs to quantitatively engineer novel cellular behaviors for environmental, biotechnological, and therapeutic purposes. Like many forms of engineering, synthetic biology projects follow a design-build-test-learn cycle: an iterative process of constructing, assaying, and modifying genetic circuits to achieve desired phenotypes. However, unlike more established forms of engineering, we do not have a quantitative set of core principles that describe the complexities of all biological activity. This limitation is pronounced in mammalian synthetic biology, where lengthy design campaigns and an incomplete understanding of the system make precisely programming cellular functions difficult. One approach to addressing challenges in synthetic biology is to increase the pace and scale of data acquisition and allow experimental data to replace hypotheses as the cornerstone of decision-making. Here, I present a suite of molecular biology and cell engineering tools that lay the foundations of a novel platform designed to enable high-throughput construction and quantitative assessment of large and complex genetic design spaces. This platform, named CLASSIC (combinatorial large-scale assembly and short-range sequencing for investigating genetic complexity), offers a novel opportunity to generate genotype- to-phenotype (G2P) maps for hundreds of thousands of multi-kilobase genetic circuits in a single experiment. We show proof-of-concept for this platform and leverage the unique ability to assay genetic diversity to optimize the performance of single-input genetic switches in mammalian cells. Additionally, we show that the CLASSIC platform can be adapted to enable image-based G2P mapping of diverse features of cellular identity and phenotype, including protein compartmentalization and cell morphology, and interactions between engineered cells in multi-cellular environments, such as T cell killing

Solar-driven thermal desalination in off-grid applications for water purification

Economic, societal, and political consequences are some of the repercussions of water scarcity. It permeates virtually all aspects of life, demonstrated by the fact that 80% of jobs are reliant on water and that disease control is achieved through prevention which highly correlates with access to quality water. Because of this, it is imperative to develop processes that generate drinking water from alternative water sources, guaranteeing constant and safe access to this vital liquid. Chapter 1 analyses the viability of desalination methods for a given region. To determine this, several factors need to be considered, such as consumption patterns, variability in water availability, and water stress. On the technical side, some are its target production capacity, feed stream quality, energy consumption, and its source. For low-scale applications with production in the tens or hundreds of liters, it is fundamental to have low-maintenance systems that are not dependent on the electrical grid, particularly in remote communities. While it is important to improve the efficiency of systems, it is also to reduce their carbon footprint by migrating to the use of alternative energy sources. This work analyses key components of water desalination technologies from 2017 to 2022 such as their efficiency, size, and used materials. Chapter 2 presents a solar-driven, membrane-less, and robust thermal system, known as Solar Thermal Resonant Energy Exchange Desalination (STREED). Its purpose is to alleviate challenges of water desalination systems, for example, a high maintenance burden due to the use of membranes, low efficiency, and high electricity input. Through the use of the concept of Resonant Energy Transfer, the efficiency of the system can be maximized by reusing the energy from the enthalpy of evaporation. This section also analyzes the production of water under a realistic solar energy profile, considering the scenario where the flow rate is constant, and the one where it is dependent on solar intensity. It was observed that by adjusting the flow rate to the present available sunlight power, water production increased by 70% for a representative week of the summer in Houston, Texas. STREED’s adaptability to an energy source that varies through time, coupled with its robustness makes it the ideal candidate to install in remote communities or developing countries

Dataset

The file contains raw data of the paper.A work investigates multimode ultrastrong coupling between cavity modes of a three-dimensional photonic-crystal cavity and the cyclotron resonance of a Landau-quantized two-dimensional electron gas in gallium arsenide.1.

Sustainable Plasmonic Photocatalysis

Throughout my Ph.D., I focused on addressing three key challenges in sustainable plasmonic photocatalysis: developing earth-abundant catalyst materials, utilizing cost-effective light sources, and optimizing industrially significant reactions. In my first project, I developed an efficient earth-abundant antenna-reactor photocatalyst for ammonia decomposition. The iron-based photocatalyst achieved efficiencies comparable to noble metals, such as ruthenium, and maintained its performance for gram-scale hydrogen production under light-emitting diode illumination. This work underscores the potential for efficient, light-driven hydrogen production using earth-abundant metals, demonstrating that plasmonic photocatalysis can activate a thermally inactive transition metal with illumination. My second project targeted methane steam reforming, a process responsible for half of global hydrogen production but also a significant source of CO₂ emissions. I developed a photocatalyst with high reactivity, selectivity, and stability for steam methane reforming. By utilizing light as the energy source and fine-tuning the selectivity of the catalysis, we achieved zero CO₂ emissions for this reaction. In my third project, I explored how the role of plasmonic photocatalysis in boosting not only the reactivity and selectivity of catalysts but also their stability. A notable observation is that catalysts display varying stability profiles when used in photocatalysis compared to traditional thermocatalysis, with illumination producing higher-energy hot carriers that enhance stability. This discovery suggests new opportunities for employing earth-abundant metals previously regarded as unreactive or unstable, paving the way for more sustainable catalytic processes

Cosmological and astrophysical probes of axionlike particles

Axionlike particles (ALPs), pseudo Nambu-Goldstone bosons arising from the spontaneous breaking of global U(1) symmetries, appear in solutions to open issues in fundamental physics and are ubiquitous in string theory compactifications. Furthermore, ALPs have a rich phenomenology that provides numerous ways to search for evidence of their existence. This work explores two potential discovery channels for ALPs. The first considers the possibility that hyperlight ALPs, with masses less than 10^(-28) eV and a Chern-Simons coupling to electromagnetism, formed a cosmic string network in the early Universe that survives beyond recombination. In this scenario, cosmic microwave background (CMB) photons passing through string loops in the network experience a rotation in their plane of polarization, an effect known as CMB birefringence that may be within reach of future CMB probes. I use existing CMB birefringence power spectrum data to constrain axion string network parameters, then discuss non-Gaussian features of axion string-induced CMB birefringence maps, and finally explore how a neural network could estimate axion string network parameters from these maps. The second potential discovery channel examines how ALPs with lepton flavor-violating couplings and masses less than 1 MeV affect the cooling rates of neutron stars. Through these studies, I develop tools that would assist in identifying signatures of ALPs in cosmological and astrophysical observations